Zero inflated negative binomial regression interpreting main and interaction effects

#1
I am running a zero inflated negative binomial model (zinb) and want to interpret the main and interaction effects.

I have the following:

People decide whether to purchase a good during a given week and I have their final purchase quantity (Min qty = 0 units and Max qty = 10 units observed from the data). Assume I am looking at the results for a particular week. I have multiple demographics variable but two discrete variables are imp namely:

education (=1 if buyer has college degree, 0 otherwise) and
gender (1 = female, 0 = male).

Due to the presence of a large number of 0's and overdispersion, I use a zinb model.
The code I use on Stata:
zinb purchase_qty i.gender##i.educ, inflate (c.age)

The regression results are (not presenting results for the inflation part here):

HTML:
purchase_qty                            Coef.    P>|z|
     1.gender                           -0.26    0.028
     1.education                        -0.07    0
     gender##education 1 1               0.12    0.027
     _cons                              -0.5     0.56
What I want to calculate from the above table is the average qty purchased by the four groups:
Group1 - gender=0 & educ=0
Group 2 - gender=1 & educ=0
Group3 - gender=0 & educ=1
Group 4 - gender=1 & educ=1.

Could someone please explain how to do this from the above output(taking into account that main effect and interaction effect are significant)?

Thanks.
 

hlsmith

Less is more. Stay pure. Stay poor.
#2
Re: Zero inflated negative binomial regression interpreting main and interaction effe

Are you familiar with logistic regression?
 

rogojel

TS Contributor
#5
Re: Zero inflated negative binomial regression interpreting main and interaction effe

hi,
the simplest way would be to use the predict functionality with the model. I do not know Stata, but I am sure it must offer predictions based on the model.

regards